Assessment of the genetic contribution to brain MRI lesion load and atrophy measures in multiple sclerosis patients

Background Multiple Sclerosis (MS) susceptibility is influenced by genetics, however little is known about genetic determinants of disease expression. We aimed at assessing genetic factors influencing quantitative neuroimaging measures in two cohorts of Progressive (PMS) and Relapsing-Remitting (RRMS) patients. Methods Ninety-nine PMS and 214 RRMS patients underwent a 3T brain MRI scan, with the measurement of five MRI metrics including T2 lesion volumes and measures of white matter, grey matter, deep grey matter and hippocampal volumes. A candidate pathway strategy was adopted: gene set analysis was carried out to estimate cumulative contribution of genes to MRI phenotypes, adjusting for relevant confounders, followed by SNP regression analysis. Results Seventeen KEGG pathways and 42 Gene Ontology (GO) terms were tested. We additionally included in the analysis genes with enriched expression in brain cells. Gene set analysis revealed a differential pattern of association across the two cohorts, with processes related to sodium homeostasis being associated with grey matter volume in PMS (p=0.002), whereas inflammatory-related GO terms like Adaptive Immune Response and Regulation of Inflammatory Response appeared associated with T2 lesion volume in RRMS (p=0.004 and p=0.008 respectively). As of SNPs, the rs7104613T mapping to SPON1 gene was associated to reduced deep grey matter volume (beta=-0.731, p=3.2*10-7 ) in PMS, while we found evidence of association between white matter volume and rs740948A mapping to SEMA3A gene (beta=22.04, p=5.5*10-6 ) in RRMS. Conclusions Our data suggest a different pattern of associations between MRI metrics and functional processes across MS disease courses, suggesting different phenomena implicated in MS.